By Kimon P. Valavanis

This e-book represents the paintings of best scientists within the box of clever keep an eye on and its functions, prognostics, diagnostics, situation dependent upkeep and unmanned platforms. The paintings offers an method of fixing engineering difficulties regarding production, automation, and particularly unmanned structures and describes contemporary advances within the disciplines pointed out above. the most target of the ebook is to illustrate how ideas and concepts from different disciplines are merged inside a standard framework utilized to the answer of advanced problems.

Show description

Read Online or Download Applications of Intelligent Control to Engineering Systems: In Honour of Dr. G. J. Vachtsevanos PDF

Best control systems books

PID Controllers for Time-Delay Systems

This monograph involves new effects at the stabilization of time-delay structures utilizing PID controllers. the most thrust of the e-book is the layout of PID controllers for time-delay structures, for which the authors have received a few very important requisites, insights and new layout ideas. one of the difficulties thought of during this booklet, an incredible one is that of stabilizing a first-order plant with useless time utilizing a PID controller.

Dynamics of Robots with Contact Tasks

As robots have gotten an increasing number of refined the curiosity in robotic dynamics is expanding. inside of this box, touch difficulties are one of the best, because contacts are found in nearly any robotic job and introduce critical complexity to method dynamics, strongly influencing robotic habit.

Robust Control Systems: Theory and Case Studies

"Robust keep an eye on structures" offers a self-contained advent to trendy keep watch over idea. It hence provides a textbook to the prevailing research-oriented literature on strong regulate. the writer lays emphasis at the glossy elements of the layout of controllers with prescribed functionality and robustness houses.

Control Problems of Discrete-Time Dynamical Systems

This monograph bargains with regulate difficulties of discrete-time dynamical platforms which come with linear and nonlinear input/output family In its current moment enlarged version the keep watch over difficulties of linear and non-linear dynamical structures might be solved as algebraically as attainable. Adaptive keep an eye on difficulties are newly proposed and solved for dynamical structures which fulfill the time-invariant .

Extra info for Applications of Intelligent Control to Engineering Systems: In Honour of Dr. G. J. Vachtsevanos

Example text

Muench, G. Kacprzynski, A. Liberson, A. Sarlashkar and M. Roemer, Model and sensor fusion for prognosis, Example: Kalman filtering as applied to corrosion-fatigue and FE models, SIPS Quarterly, Review Presentation, 2004. 1 Prognostic Methods with Application to an Integrated Health Management System 21 19. Ray, 1996. 20. R. Schauz, Wavelet neural networks for EEG modeling and classification, PhD Thesis, Georgia Institute of Technology, 1996. 21. A. Schömig and O. Rose, On the suitability of the Weibull distribution for the approximation of machine failures, in Proceedings of the 2003 Industrial Engineering Research Conference, May 18–20, Portland, OR, 2003.

Hierarchical reasoners have a “built-in” data management capability for containing erroneous information and utilizing multiple data and information sources. 5. Ability to capture and localize system degradations (as opposed to only hard failures), based on increased health awareness of the lowest-level LRUs, hence providing a more accurate vehicle availability assessment. 1 Prognostic Methods with Application to an Integrated Health Management System 19 Fig. 14 Distributed prognostic system architecture.

Orchard et al. ), F (x(t), t, U ) is a general time-varying nonlinear function, y(t) represents feature measurements, and ω1 (t), ω2 (t) and υ(t) are white noises (not necessarily Gaussian). The nonlinear function F (x(t), t, U ) may represent a model based on first principles, a neural network, or even a fuzzy system. 3) j =t +1 t +p N (i) ≈ wt (i) p(xt +1 | xt ) ··· p(xj | xj −1 ) dxt +1:t +p−1. j =t +2 i=1 The evaluation of these integrals, though, may be difficult and/or may require significant computational effort.

Download PDF sample

Rated 4.13 of 5 – based on 21 votes